Cardiovascular risk in US adults with nonalcoholic steatohepatitis (NASH) vs. matched non-NASH controls, National Health and Nutrition Examination Survey, 2017–2020

Background NASH is considered a contributor to atherosclerotic cardiovascular disease (ASCVD) risk; however, its contribution beyond traditional risk factors for CVD, particularly diabetes, is less clearly understood. This study aimed to quantify the cardiovascular-event risk associated with NASH, independent of diabetes status. Methods A cross-sectional analysis was conducted using the 2017–2020 NHANES pre-pandemic cycle. NASH was defined based on presence of steatosis without other causes of liver disease, and FibroScan+AST score from vibration-controlled transient elastography (VCTE). Significant fibrosis (stages F2-F4) was identified by liver stiffness measurement from VCTE. Predicted primary CV-event risk was estimated using both the Pooled Cohort Equations (PCE) and the Framingham Risk Score (FRS). NASH patients were matched with non-NASH controls on age, sex, race/ethnicity, and diabetes status. Weighted logistic regression was conducted, modeling elevated predicted CV risk (binary) as the dependent variable and indicators for NASH / fibrosis stages as independent variables. Results A sample of 125 NASH patients was matched with 2585 controls. NASH with significant fibrosis was associated with elevated predicted 10-year CV risk, although this association was only statistically significant in PCE analyses (odds ratio and 95% CI 2.34 [1.25, 4.36]). Analyses restricting to ages <65 years showed similar results, with associations of greater magnitude. Conclusion Independent of diabetes, a significant association was observed between NASH with significant liver fibrosis and predicted primary CV-event risk in US adults, particularly for those <65. These findings suggest the importance of accounting for NASH and liver-fibrosis stage in predicting CV-event risk.


Introduction
Non-alcoholic fatty liver disease (NAFLD) is a condition believed to affect more than 25% of adults worldwide, [1] in which excess fat is stored in the liver (hepatic steatosis), exceeding 5%-10% of the liver's weight.NAFLD is not attributable to other causes of chronic liver disease [2,3] further classified into non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH).NASH is distinguished from NAFL by presence of inflammation and hepatic injury [2,3].It has been estimated that approximately 20%-30% of people with NAFLD have NASH [4].
NASH is an increasingly significant public health concern in the US [5].Current estimates of NASH in US adults suggest a prevalence of 5% to 6%, [6][7][8] but it has been observed to range from approximately 1% [9] to 12% [10].The prevalence has risen over the past decade, [9] and is expected to continue to increase substantially in future [11].Progression of NASH is recognized to lead to cirrhosis, followed by potential decompensation (i.e., liver failure) and hepatocellular carcinoma (HCC) [12].
Beyond the liver-related complications of NAFLD/NASH, increasing evidence has emerged in recent years of the association with multisystem disease affecting a variety of extra-hepatic organ systems, including cardiovascular [13,14].NAFLD is recognized to be a risk factor for atherosclerotic cardiovascular disease (CVD), which is a principal cause of death in NAFLD patients [13].Although the mechanism for the relationship between CVD and NAFLD remains under investigation, the pathophysiology associated with inflammation in fibrotic NASH may exacerbate insulin resistance and dyslipidemia in tandem with a release of proinflammatory, vasoactive, and thrombogenic factors that may promote the development of CVD [6].
The association of NAFLD/NASH and CVD is recognized in a recent scientific statement by the American Heart Association (AHA), [1] emphasizing that NASH enhances cardiovascular risk.The AHA notes that research has demonstrated that NASH has an incremental adverse impact on atherosclerotic cardiovascular disease (ASCVD) risk, beyond traditional risk factors.However, NASH is currently categorized as a risk enhancer, as the AHA statement notes that the risk-modulating effect has not been quantified numerically.
Growing evidence suggests that NAFLD may both increase the risk of incident T2D by exacerbating hepatic insulin resistance, and worsen glycemic control in patients with T2D, contributing to risk of progression of T2D to important chronic complications such as CVD and chronic kidney disease [15].T2D is considered a major risk factor for CVD, [16,17] and to be bi-directionally associated with NAFLD, [15] potentially confounding the estimation of CVD risk associated with NASH.
A related, additional challenge in numerical quantification of excess CV-event risk associated with NASH is that current CV-risk prediction equations do not account for possible risk factors involved in the relationship between NASH and CVD.As noted by the AHA, while risk equations such as the Pooled Cohort Equations and Framingham Risk Score are commonly used in the general population, their utility in persons with NASH is not well-established [1].The association of NAFLD/NASH with CVD has been observed independently of traditional risk factors, such as those included in these risk equations (i.e., blood pressure, diabetes, and dyslipidemia) [18][19][20][21].For example, body mass index/obesity is not included in current CV-risk prediction equations; however, it has been hypothesized that ectopic fat deposition in the liver (i.e., NAFLD) and other tissues may be associated with increased CVD risk beyond that attributable to traditional risk factors [1].Additionally, the risk of CVD in NAFLD/NASH has also been shown to be particularly elevated in those with advanced or significant fibrosis, [22][23][24] although fibrosis is not included in current risk equations.
Estimation of excess CV-event risk associated with NASH, as well as addressing potential confounding of T2D, may help inform clinical understanding of the relationship between NASH and CVD.Accordingly, this analysis sought to estimate the association of NASH with risk of a primary CV event, independent of diabetes status.This analysis was undertaken by estimating the predicted 10-year probability of a first cardiovascular event using published risk equations in persons predicted to have NASH, comparing to that in non-NASH controls, matching on diabetes status and other demographic factors.To explore potential drivers of the association of NASH with CV risk, the incremental CV risk was evaluated for NASH overall as well as by estimated fibrosis stages (no fibrosis or minimal fibrosis vs significant fibrosis).

Data source and study design
This was a cross-sectional study using data from the 2017 to March 2020 pre-pandemic continuous National Health and Nutrition Examination Survey (NHANES) cycle.NHANES data are made publicly available by the National Center for Health Statistics (NCHS) and include participants from the non-institutionalized civilian US population.Sample weights are needed to account for the complex survey design/oversampling, survey non-response, and post-stratification adjustment to align with Census counts.Weighting of the NHANES data is expected to produce estimates representative of the civilian resident non-institutionalized US population.
Due to the COVID-19 pandemic, the 2019-2020 survey cycle was not completed.However, NCHS combined the 2019-2020 partial data with the previous 2017-2018 cycle data to create the 2017 to March 2020 pre-pandemic cycle.This survey cycle covers a 3.2-year period (compared with the previous 2-year survey cycles) and can be weighted to provide nationally representative estimates as in previous survey cycles [25].In the 2017-2018 cycle, NHANES included for the first time measures of liver stiffness and steatosis from vibration controlled transient elastography (VCTE), which were then supplemented with measures from 2019-2020 in the 2017-2020 cycle.This study therefore used the 2017-2020 NHANES cycle, to leverage additional sample and to improve data recency vs. the 2017-2018 cycle alone.The 2017-2020 NHANES cycle includes survey interview responses for 15,560 participants, of whom 14,300 completed the medical examination.

Study population
The analytic sample was determined through a combination of complete case variables availability, and either identified as NASH or exact matched as a non-NASH control (Fig 1).Eligibility was restricted to participants who completed the NHANES medical examination, were not pregnant, were �30 years of age, had complete data for variables required for prediction of NASH status, had no history of atherosclerotic CVD (ASCVD-defined as CHD, MI, stroke or angina) or heart failure (HF), and had complete data for inputs of the risk equations for a primary CV event.Eligible participants were then restricted to only those identified as NASH and non-NASH exact matched controls for the analytic sample.

Prediction of NASH
Prediction of NASH was conducted using a multistep approach, similar to other NHANES studies, [27,28] based on presence of presumed NAFLD, indicated by steatosis (CAP � 302 dB/m) and no alternative common cause of liver disease (i.e., excessive alcohol consumption, hepatitis B or C); [29] and FibroScan-aspartate aminotransferase (FAST) score �0.48, to predict NASH among those with presumed NAFLD [30].In a population with biopsy-proven NAFLD, FAST scores �0.48 have been reported to predict definite NASH (NAFLD Activity Score [NAS] �5) with area under the receiver operating characteristic curve (AUC) of 0.752, sensitivity of 80.3%, specificity of 58.2%, positive predictive value (PPV) of 62.7%, and negative predictive value (NPV) of 77.2% [30].This threshold also reflects the approximate midpoint of the rule-out (�0.35) and rule-in (�0.67) cutoffs reported for the FAST score for predicting atrisk NASH (NAS �4 and fibrosis stage �2) in patients with suspected NAFLD, [31] suggesting that the sample predicted to have NASH in this analysis may lean towards higher fibrosis stages.
A multi-society and multi-stakeholder consensus revision of the NAFLD nomenclature occurred with the results as follows: Steatotic Liver Disease (SLD) with sub-classifications of Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) and Metabolic dysfunction Associated Steatohepatitis (MASH) [29].While developments in the classification of NAFLD/NASH were considered during the conduct of this analysis, to maintain consistency with the context and motivation established by the aforementioned AHA scientific statement, [1] NASH was kept as the exposure of interest in the analysis.

Prediction of CV risk
The primary analysis calculated the 10-year probability of a primary CV event for each study participant using the 2013 ACC/AHA Pooled Cohort Equations (PCE) [16].The PCE predicts risk of a first ASCVD event defined as CHD death, nonfatal MI, and both fatal and nonfatal stroke.The following variables are included in the PCE: age, total cholesterol, high-density lipoprotein cholesterol (HDL-c), systolic blood pressure (SBP), SBP treatment, smoking status, and diabetes status.
Sensitivity analyses used the 2008 Framingham Risk Score (FRS) [17].Although the same variables are included in both the PCE and FRS, the outcomes that are modeled and the form of the equations differ.The FRS predicts risk of a first CV event defined as CHD: coronary death, myocardial infarction, coronary insufficiency, and angina; cerebrovascular events: including ischemic stroke, hemorrhagic stroke, and transient ischemic attack; peripheral artery disease (intermittent claudication); and HF.
The FRS was validated in participants aged 30-74 years of age with no race/ethnicity restrictions, whereas the PCE was validated in non-Hispanic (NH) Black and White participants aged 40-79 years.However, the existing literature suggests that the PCE has good discrimination in Hispanic and Asian populations (even though calibration is limited for all races/ethnicities) [33,34].Accordingly, to increase both sample size and generalizability, analyses using the PCE did not restrict race/ethnicity.Additionally, main analyses included participants aged �30 years.However, sensitivity analyses were conducted for analyses of the PCE that restricted to NH Black and White participants aged �40 years.Because the performance of CV risk equations has been shown to worsen with increasing age, [35] we conducted additional sensitivity analyses for both risk equations that narrow the age range to those <65 years.

Covariates
In NHANES, the following variables were self-reported by the participant: age, sex, race/ethnicity, current smoking, diabetes (self-reported physician diagnosis), blood pressure treatment, and history of hepatitis B or C.
Various laboratory measurements were used in this analysis for calculation of predicted CV risk and prediction of NASH status.Total cholesterol, triglycerides, alanine transaminase (ALT), and aspartate transferase (AST) were measured using an enzymatic method, HDL-c was measured using the direct method, and platelets were measured from whole blood.LDL-c was calculated using the Friedewald equation [36].FIB-4 was calculated as age x AST / (platelets x p (ALT)) [37].Three consecutive blood pressure measurements were taken 60 seconds apart and were averaged (for diastolic and systolic BP, separately) to obtain the measurement used for analysis.Height, weight, and waist circumference were recorded by trained health technicians.BMI was calculated from measured weight and height as kg/m 2 .Obesity was defined as BMI �30 kg/m 2 .
Matching performance was evaluated by assessing the standardized mean differences (SMD) of the weighted covariates in NASH versus non-NASH participants before and after matching.After matching, all covariates were within the 0.1 recommended SMD threshold, [38] with all except sex within 0.05.
Demographic and clinical characteristics were summarized and compared in participants with NASH and matched non-NASH participants.Weighted proportions (for categorical variables) and weighted means (for continuous variables) with corresponding standard errors were reported.P-values were calculated using survey-weighted chi-square tests with the Rao-Scott correction for categorical variables and survey-weighted t-tests for continuous variables.
Weighted logistic regression was used to evaluate the association between NASH and 10-year predicted CV risk as a binary variable.Ten-year predicted CV risk was defined as elevated if �7.5% in analyses using the PCE, and if �20% for analyses using the FRS, based on treatment guidelines [39].NASH (the independent variable of interest) was modeled in two ways: as a binary variable (NASH vs. no NASH) and as a categorical variable (NASH with significant fibrosis, NASH with no/minimal fibrosis, and no NASH [reference group]).Odds ratios and corresponding 95% CIs were obtained.P-values from Wald tests were also calculated.Analyses were conducted overall and restricted to participants aged <65 years.A secondary analysis used linear regression to estimate the association between NASH and 10-year predicted CV risk as a continuous variable.
For all final models, sampling weights and the Taylor series linearization variance approximation method were used to obtain point estimates and corresponding standard errors.
All statistical analyses were conducted using R (version 4.2.0).

Compliance with ethics guidelines
The analysis reported is based on public-use data and does not contain any new studies with human participants or animals performed by any of the authors.

Matching
An unweighted sample of 125 participants was predicted to have NASH, then exact matched with 2585 non-NASH participants.In the matched sample, compared with participants without NASH, those with NASH were more likely to be obese (85% vs. 42%), hypertensive (65% vs. 42%), have low HDL-c (57% vs. 31%), and were less likely to be a current smoker (7% vs. 18%) (all p < 0.01) (Table 1).As expected, a significantly higher proportion of participants with NASH had significant fibrosis (75% vs. 10%, p < 0.01).2).Results were similar in sensitivity analyses for the PCE that restricted to NH Black and White participants aged �40 years: point estimates were comparable, but not all associations were statistically significant due to a decrease in sample size.
Analyses restricted to participants under 65 years of age showed similar results, but associations were of greater magnitude and statistically significant with the PCE.Compared to participants with no NASH, those with NASH and significant fibrosis had 3.04 times the odds of having elevated predicted CV risk as calculated using the PCE (95% CI: 1.43, 6.44) and 2.02 times the odds as calculated using the FRS (95% CI: 0.61, 6.68) (Table 3).
Additional sensitivity analyses that evaluated 10-year predicted CV risk as a continuous variable using linear regression resulted in null associations in the overall cohort (S1 Table in S1 File).However, when restricting to participants <65 years of age, NASH with significant fibrosis was associated with statistically significant higher incremental predicted CV risk in FRS as compared with no NASH (PCE: 1.4% [0.00%, 3.20%] and FRS: 2.9% [0.18%, 5.68%] To explore potential for bias from sample non-response, an exploratory analysis was conducted to assess the impact of reweighting the analytic sample for differences in age, sex, and race/ethnicity.This was found to have minimal impact, with limited change in effect magnitudes, and no change in statistical significance of results.

Discussion
In this analysis, NASH was associated with higher 10-year predicted CV risk independent of diabetes.This association was more notable and of greater magnitude in persons with more severe liver fibrosis (i.e., estimated stages F2-F4) and persons under 65 years of age.These findings are important given patients with NASH have been shown to have more rapid liver fibrosis progression compared to those with NAFL.A systematic review and meta-analysis found that one in five patients who progress could be considered rapid progressors (transition from stage 0 to stage 3-4 fibrosis within an average of six years) [40].
According to the AHA, there is currently limited US population-based data on CV risk in NASH, and CV risk associated with NASH has not been well quantified.Several previous studies have matched individuals with NAFLD/NASH to those without NAFLD/NASH to evaluate the association with CVD [18,20,21,41].These studies have generally matched on age and sex, with subsequent adjustment for CVD risk factors.Most reported an increased risk of CVD in patients with NAFLD/NASH when compared with those without.However, these studies consisted of varying populations (adults vs children/young adults; a variety of geographic locations, different definitions of NAFLD/NASH, and different outcome definitions (MACE [20], CVD [defined as ischemic heart disease or stroke], [18] acute MI/stroke, [41] coronary artery disease, [14] and right ventricular dysfunction [21]).
One advantage of this study is its use of established CV risk equations to evaluate the potential for elevated CV risk in NASH.The PCE and FRS remain standard CV risk equations used in clinical practice; but when the PCE or FRS (and most other) CV risk scores are applied to contemporary cohorts, the PCE and FRS have been shown to overestimate CV risk [35,42].There is variability across risk scores with regard to outcome definitions (and correspondingly, predicted risks), which can impact which patients are identified as high-risk and are targeted for preventive therapy [43].The fact that associations were more frequently found in PCE analyses may show a higher association with ASCVD than with outcomes included in FRS but not PCE such as atrial fibrillation or heart failure.Additionally, the performance of CV risk prediction equations that have been developed in a general population has not been well-studied in NAFLD/NASH populations.A recent study evaluated the performance of the PCE in persons with and without NAFLD and found that discrimination was worse in NAFLD, and calibration was poor overall.Observed CV risk was higher than predicted CV risk in persons with NAFLD (i.e., predicted CV risk was underestimated), and vice versa for those without NAFLD [44].If predicted CV risk is overestimated in non-NAFLD/non-NASH and underestimated in NAFLD/NASH, then it is possible that the association between NASH and CV risk is of greater magnitude than suggested in this study, as our outcome was predicted CV risk.Further, as the risk equations used in this study do not account for potential mediators of the relationship between NASH and CV risk, such as liver fibrosis [22][23][24] and ectopic fat, [1] estimated CV risk may be further underestimated.
An important consideration in our study was the inclusion of diabetes in the matching algorithm.Components of metabolic syndrome including obesity, hypertension, dyslipidemia, and insulin resistance/T2D are recognized to be pre-disposing conditions for NASH, [29] and these components are associated with CV risk [15][16][17].However, these conditions may also mediate the association of NASH and CV risk along the causal pathway, as recent evidence suggests a bi-directional relationship between NAFLD and metabolic syndrome [13].For this reason, some previous studies have not matched on diabetes.By matching on diabetes, we have ensured that we have removed any potential confounding related to the condition.Consequently, it is possible that we may have removed some of the indirect effects of NASH on predicted CV risk that is mediated by diabetes.However, provided that we still found an association, this suggests that an effect of NASH on predicted CV risk still remains, above and beyond that either confounded or mediated by diabetes.
Our study had several limitations.First, because VCTE measurements are only available in recent continuous NHANES cycles, we could not leverage data from earlier cycles, which resulted in limited sample size for the analysis, which may impact the reliability of estimates.We have indicated estimates that may be unreliable and should be interpreted with caution.Nonetheless, these results provide insight into a topic that warrants further study with larger samples; incorporating VCTE measurements collected in future cycles of NHANES may help address uncertainty in results of this analysis.A second limitation is that the cross-sectional nature of the data prevented validation of predicted CV risk (i.e., based on longitudinal observations of CV events).Third, there were potential limitations in determining NASH and fibrosis status through non-invasive tests rather than liver biopsy, although this approach is consistent with other recent studies [45].In addition, certain variables in the analysis relied on self-reported data, which could result in misclassification.If these variables were underreported, this analysis may have incorrectly included some participants with other liver diseases in the NASH group.Among participants identified as having presumed NAFLD, use of FAST score �0.48 to predict NASH should be interpreted in relation to the predictive accuracy (i.e., sensitivity, specificity, PPV, and NPV) described earlier.Fourth, currently, there are no consensus cutoffs for fibrosis stages as measured by VCTE in NAFLD/NASH [46,47].Fifth, given the small number of participants with NASH with no/minimal fibrosis (n = 30 in the main analysis and n = 26 in the analysis that restricts to adults aged 30-64 years), we refrain from interpreting this category as per NHANES analytic guidelines.In addition, limited sample size of NASH patients aged 65 and older (n = 25) prevents us from examining that subgroup in further detail.Although this research was conducted to align with the AHA statement, future studies could seek to confirm these findings in MASLD and MASH populations.Finally, although we concluded that NASH was associated with higher predicted CV risk independent of diabetes, this study cannot rule out potential residual confounding by other conditions commonly comorbid with NASH (e.g., obesity).

Conclusion
In this study, a significant association between NASH and primary CV event risk was observed, independent of diabetes, particularly in adults between 30 and 64 years of age.The incremental risk was greater for estimated fibrosis stages F2-F4, suggesting the importance of accounting for fibrosis stage in predicting CV risk.This analysis suggests that NASH with significant fibrosis confers increased CV risk above that associated with diabetes.

Table 2 . Association of NASH and estimated fibrosis stages with elevated predicted CV risk, in adults aged �30 and matched to non-NASH controls.
NASH controls matched on age, sex, race/ethnicity, and diabetes status.Odds ratios and corresponding 95% confidence intervals and p-values were obtained using weighted univariate logistic regression.Participants with estimated fibrosis stage of F2 or higher (i.e., LSM �8.2) were considered to have significant fibrosis, while estimated stages F0-F1 (i.e., LSM <8.2) were considered no/minimal fibrosis. https://doi.org/10.1371/journal.pone.0309617.t002

Table 3 . Association of NASH and estimated fibrosis stages with elevated predicted CV risk, in adults aged 30-64 and matched to non-NASH controls.
NHANES analytic guidelines recommend unweighted sample size �30 for reporting proportions, means, and variances; reliability of these estimates should be interpreted with caution.NASH and non-NASH controls matched on age, sex, race/ethnicity, and diabetes status.Odds ratios and corresponding 95% confidence intervals and p-values were obtained using weighted univariate logistic regression.Participants with estimated fibrosis stage of F2 or higher (i.e., LSM �8.2) were considered to have significant fibrosis, while estimated stages F0-F1 (i.e., LSM <8.2) were considered no/minimal fibrosis.